clusterVisualNone-class {goCluster} | R Documentation

## Class "clusterVisualNone", a placeholder for the goCluster visualization methods

### Description

The class can be used to avoid specifying a visualization method when performing an analysis with `goCluster`.

### Slots

All slots are described in the documentation for the `clusterModule-class`.

### Extends

Class `"clusterVisual"`, directly. Class `"clusterModule"`, by class `"clusterVisual"`.

### Methods

config
  `signature(object = "clusterVisualNone")`: The class has no parameters. This method does not result in any action.
execute
  `signature(object = "clusterVisualNone")`: The class has no executable function defined and will do nothing.
setup
  `signature(object = "clusterVisualNone")`: The class has no parameters. This method returns an empty list.
setup<-
  `signature(object = "clusterVisualNone")`: The class has no parameters. This method does not result in any action.
reset
  `signature(object = "clusterVisualNone")`: resets the results of this class so that the analysis can be run again.
display
  `signature(object = "clusterVisualNone")`: generates the actual graphic for this object.
print
  `signature(x = "clusterVisualNone")`: prints generic information about the object.

### Author(s)

Gunnar Wrobel, http://www.gunnarwrobel.de.

### See Also

`goCluster-class`, `clusterModule-class`, `clusterVisual-class`

### Examples

    set.seed(1000)

    data(benomylsetupsmall)

    a <- new("goCluster")

    ## This will result in an object without visualization
    execute(a) <- benomylsetupsmall

    ## We can choose and add the visualization method afterwards

    ## Create the visualization method
    b <- new("clusterVisualHeatmap")

    ## Assign the new method to the old goCluster object
    a@visu <- b

    ## Prepare the visualization
    a@visu <- execute(a@visu, a)

    if(interactive()){
    ## This example can only be run in an interactive mode

    ## This plot shows only four genes since the loaded dataset
    ## has been reduced to only 100 genes. Try the same with
    ## the full dataset
    display(a, selection = "GO:0003735")
    }

[Package goCluster version 1.0.3 Index]